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Is your portfolio ready for market turbulence? Discover how risk simulations can reveal portfolio sensitivity, key risk metrics, and performance under past crises. Gain insights to optimize risk management and make more confident investment decisions.
Have you ever thought about how your current portfolio would behave during historical market crises and events, or have you tried doing any simulations or stress tests on your portfolios and asset classes? What is the tracking error of your portfolio relative to your own benchmark indices? These questions arise periodically with our clients, and we have developed a solution for that.
We are currently in a very interesting market situation, as concerns about the possible overvaluation of technology companies have risen with the Chinese AI startup developing affordable and efficient AI models. This has sparked new concerns and discussions in the market and the weights of magnificent 7’s and US tech allocations as well as the threats and opportunities surrounding Trump's second inauguration.
Now you have the opportunity to simulate your portfolio through crises with Jay, such as the Financial Crisis of 2008, Covid-19, or the Dot-com bubble of 2000.
We have developed a portfolio analysis in Jay, where you can quickly see the key ratios such as Sharpe ratio, tracking error, beta, and alpha, besides sensitivity to historical events. But how can these benefit you in portfolio management?
Besides monitoring the key ratios, crisis simulation is a really good tool for risk management to help you understand how your portfolio might behave under extreme market conditions, allowing you to prepare for potential downside risks and to be aware of how long it would take for the portfolio to recover from a market drop.
What do we need to calculate to ensure that generating the report is as easy and effortless as possible for the client, just one click away?
In order to model the portfolio during historical crises, we have built an index portfolio that closely resembles the original portfolio. The index-based portfolio allocation aims to closely represent the actual risk distribution of the real investment portfolio. The index portfolio is created by finding the most representative index for each instrument in the portfolio using an algorithm developed by Jay. The algorithm is based on linear regression and security classification information. Afterward, the index is weighted so that its movements align as closely as possible with the described instrument (beta adjustment). The sum of these risk-weighted indices forms the index portfolio.
R² indicates how well an individual security or portfolio correlates with the indices. The significance level of the correlation coefficient can be used to assess the statistical significance of the coefficient. In Jay, we use the square of Pearson's correlation coefficient (r²). For example, if r² = 0.76, it means that the explanatory variable explains 76% of the variance of the dependent variable.
The market risk report is part of our advanced analytics and risk services, which includesa wide range of high-quality analyses, for example, VaR report, scenario analyses and efficient frontier modeling. If you are interested in exploring these reports for your portfolio, please reach out and we´d be happy to arrange a demo presentation and provide a trial period. Contact us
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